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All Journal Building of Informatics, Technology and Science Scientica: Jurnal Ilmiah Sains dan Teknologi
Triningsih, Elsa
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Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Other

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Audit Tata Kelola Teknologi Informasi Perpustakaan Universitas Islam Negeri Sultan Syarif Kasim Riau Menggunakan Framework COBIT 2019 Triningsih, Elsa; Faizah, Muhimmatul; Yulianti, Nelvi; Megawati, Megawati
Scientica: Jurnal Ilmiah Sains dan Teknologi Vol. 2 No. 8 (2024): Scientica: Jurnal Ilmiah Sains dan Teknologi
Publisher : Komunitas Menulis dan Meneliti (Kolibi)

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Abstract

Perpustakaan UIN SUSKA Riau menggunakan katalog online Online Public Access Catalog (OPAC) untuk membantu pengunjung menemukan buku sebagai sumber bacaan. Namun Perpustakaan UIN SUSKA Riau belum memiliki indikator yang dapat merepresentasikan bahwa kinerja teknologi informasi sesuai dengan tujuan yang ingin dicapai. Oleh karena itu, untuk mengetahui kinerja TI perlu dilakukan analisis tata kelola  TI. Tujuannya adalah untuk menentukan tingkat kinerja, melakukan analisis nilai dan membuat rekomendasi perbaikan. Penelitian ini menggunakan wawancara dan kuesioner. Framework COBIT 2019 menggunakan domain proses APO04 (Managed Innovation), DSS01 (Managed Operations), dan DSS05 (Managed Security Services).Penelitian ini bertujuan untuk mengetahui tingkat kinerja Online Public Access Catalog (OPAC) Perpustakaan UIN Suska Riau untuk setiap domain proses. Yang mana didapat kan hasil APO04 berada pada level 3 dengan kategori L (large achieved) dan DSS01 berada pada level 4 dengan kategori L (large achieved)). Sedangkan pada domain DSS05 berada pada level 4 dengan kategori L (large achieved).
Analisis Sentimen Terhadap Program Makan Bergizi Gratis Menggunakan Algoritma Machine Learning Pada Sosial Media X Triningsih, Elsa; Afdal, M; Permana, Inggih; Rozanda, Nesdi Evrilyan
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6534

Abstract

The government has launched the Free Nutritious Meal Program as part of a strategic effort to reduce stunting in Indonesia. However, the program has generated a lot of controversy among the public, especially regarding the large budget allocation that is considered burdensome and its impact on the education sector and the country's financial stability. This study aims to analyze public sentiment towards the program by utilizing data from social media platform X (Twitter) as much as 2,400 data. Public sentiment is classified into three categories, namely positive, negative, and neutral, using two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest. In addition, the SMOTE technique is used to handle data imbalance in the model training process. The analysis results showed that negative sentiments dominated at 46%, with the main issue highlighted being the high budget allocation and its impact on education. In terms of performance, the SVM algorithm with SMOTE produced the highest accuracy of 85.74%, outperforming the Random Forest algorithm which only achieved 81.53% accuracy.
Co-Authors Faizah, Muhimmatul Inggih Permana M Afdal Megawati - Rozanda, Nesdi Evrilyan Yulianti, Nelvi